How to remove a specific value from two list if they exclude a given euclidean distance?-CodePudding

I have these two lists of data x & y. Now I want to remove the specific cartesian point (x,y) which has more than a specific euclidean distance(Example: 4). How to do that?

x = [92.5 , 92.75 ,92.75, 93. ,  93.,   93.25 ,93.25, 93.25,
 93.25 ,93.25 ,93.25 ,93.25 ,93. ,  92.5,  93.  , 93.  , 93.,  
 92.5 , 92.75, 93.  , 93.25, 93.25 ,93.5  ,93.5 , 93.5  ,93.5 , 
 91.5 , 92.5  ,92.5  ,92.5 , 92. ,  92.,   92.  , 91.75 ,91.5 , 
 91.5 , 91.25 ,91.  , 91.25 ,91.25, 91.25 ,91.]

y = [17.75, 17.75 ,18. ,  18. ,  18.  , 18.25, 18.25 ,18.5,
18.5 , 18.5 , 18.75 ,18.75 ,18.75, 24.75 ,19. ,  18.75, 18.75, 
 18.75 ,18.75 ,18.75 ,19.   ,19. ,  19.25, 19.5 , 19.5 , 19.75 ,
 24.25 ,24.75 ,24.75 ,24.75 ,24.25, 24.25 ,24.25 ,24.25 ,24.75, 
 24.25 ,23.75, 23.75 ,23.75 ,24.25 ,23.75 ,23.75]

This is what I did, but didn't work out.

for k in range(len(x)):
  x1 = x[k]
  y1 = y[k]
  x2 = x[k 1]
  y2 = y[k 1]

  distance = np.sqrt((x2-x1)**2 (y2-y1)**2)
  
  if distance>4:
    x.remove(k)
    y.remove(k)

CodePudding user response：

this can solve your issue,

import numpy as np

newX, newY = [], []
for k in range(len(x) - 1):
    if np.sqrt((x[k   1] - x[k]) ** 2   (y[k   1] - y[k]) ** 2) <= 4:
        newX.append(x[k])
        newY.append(y[k])

newX:

[92.5, 92.75, 92.75, 93.0, 93.0, 93.25, 93.25, 93.25, 93.25, 93.25, 93.25, 93.25, 93.0, 93.0, 93.0, 92.5, 92.75, 93.0, 93.25, 93.25, 93.5, 93.5, 93.5, 91.5, 92.5, 92.5, 92.5, 92.0, 92.0, 92.0, 91.75, 91.5, 91.5, 91.25, 91.0, 91.25, 91.25, 91.25]

newX:

[17.75, 17.75, 18.0, 18.0, 18.0, 18.25, 18.25, 18.5, 18.5, 18.5, 18.75, 18.75, 19.0, 18.75, 18.75, 18.75, 18.75, 18.75, 19.0, 19.0, 19.25, 19.5, 19.5, 24.25, 24.75, 24.75, 24.75, 24.25, 24.25, 24.25, 24.25, 24.75, 24.25, 23.75, 23.75, 23.75, 24.25, 23.75]

CodePudding user response：

It won't be a good idea to change the list on which the loop is running. This code might help you

x = [92.5 , 92.75 ,92.75, 93. ,  93.,   93.25 ,93.25, 93.25, 93.25 ,93.25 ,93.25 ,93.25 ,93. ,  92.5,  93.  , 93.  , 93., 92.5 , 92.75, 93.  , 93.25, 93.25 ,93.5  ,93.5 , 93.5  ,93.5 , 91.5 , 92.5  ,92.5  ,92.5 , 92. ,  92.,   92.  , 91.75 ,91.5 , 91.5 , 91.25 ,91.  , 91.25 ,91.25, 91.25 ,91.]
y = [17.75, 17.75 ,18. ,  18. ,  18.  , 18.25, 18.25 ,18.5, 18.5 , 18.5 , 18.75 ,18.75 ,18.75, 24.75 ,19. ,  18.75, 18.75, 18.75 ,18.75 ,18.75 ,19.   ,19. ,  19.25, 19.5 , 19.5 , 19.75 , 24.25 ,24.75 ,24.75 ,24.75 ,24.25, 24.25 ,24.25 ,24.25 ,24.75, 24.25 ,23.75, 23.75 ,23.75 ,24.25 ,23.75 ,23.75]
x_tmp, y_tmp = [], []
for k in range(len(x)-1): # Till len(x) will give index out of range error
    x1, x2, y1, y2 = x[k], x[k 1], y[k], y[k 1]
    distance = np.sqrt((x2-x1)**2 (y2-y1)**2)
    if distance<=4:
        x_tmp.append(x[k])
        y_tmp.append(y[k])
print(x_tmp, y_tmp)

Also, where have you defined 'i'.

CodePudding user response：

Faster, concise solution:

dists = np.sqrt(np.diff(x)**2   np.diff(y)**2)
mask = np.nonzero(dists <= 4)[0]

new_x = x[mask]
new_y = y[mask]

For this you'd need to convert your lists to numpy arrays first: x = np.array(x).

This solution is equivalent to the others presented in this thread.